基于改进的EMD交流接触器退化特征参数信号消噪处理方法
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摘要
针对交流接触器退化特征参数提取过程中,扰动信号会影响交流接触器电寿命状态预测的准确性,提出了一种将经验模态分解(EMD)的阈值方法与Savizky-Golay滤波方法相结合的改进的EMD消噪方法。首先,用新小波阈值函数对EMD分解的高频本征模态分量进行消噪处理,可以保持交流接触器退化特征参数信号的高频分量;其次,用Savizky-Golay滤波对EMD分解的低频本征模态分量进行滤波降噪处理,可以较好地保持交流接触器退化特征参数信号低频分量的光滑特性;最后,将消噪后的高频分量与低频分量叠加重构,得到消噪后的信号。试验结果表明,改进的EMD消噪方法能够有效剔除强噪声,为交流接触器电寿命预测提供更精确的数据。
As the disturbance would affect the accuracy of AC contactor electrical life prediction during the extraction of the degraded characteristic parameters of AC contactor,this paper proposed an improved EMD denoising method based on empirical mode decomposition(EMD) and Savizky-Golay filtering.Firstly,the denoising method of the new wavelet threshold function is used to denoise the high frequency eigenmode component of the EMD decomposition,so that the high frequency component of the AC contactor degradation characteristic parameter signal can be maintained.Secondly,the Savizky-Golay filter is used to perform filtering and noise reduction on the low-frequency eigenmode components of the EMD decomposition,which can better maintain the smooth characteristics of the low-frequency components of the degraded characteristic parameter signal of the AC contactor.Finally,the de-noised high-frequency component and the low-frequency component are superimposed and reconstructed to obtain the denoised signal.The test results show that the improved EMD method can effectively eliminate strong noise and thus provide more accurate data for AC contactor electrical life prediction.
As the disturbance would affect the accuracy of AC contactor electrical life prediction during the extraction of the degraded characteristic parameters of AC contactor,this paper proposed an improved EMD denoising method based on empirical mode decomposition(EMD) and Savizky-Golay filtering.Firstly,the denoising method of the new wavelet threshold function is used to denoise the high frequency eigenmode component of the EMD decomposition,so that the high frequency component of the AC contactor degradation characteristic parameter signal can be maintained.Secondly,the Savizky-Golay filter is used to perform filtering and noise reduction on the low-frequency eigenmode components of the EMD decomposition,which can better maintain the smooth characteristics of the low-frequency components of the degraded characteristic parameter signal of the AC contactor.Finally,the de-noised high-frequency component and the low-frequency component are superimposed and reconstructed to obtain the denoised signal.The test results show that the improved EMD method can effectively eliminate strong noise and thus provide more accurate data for AC contactor electrical life prediction.
引文
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[6] 李奎,李晓倍,郑淑梅,等.基于BP神经网络的交流接触器剩余电寿命预测[J].电工技术学报,2017,32(15):120-127.
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[11] 李清泉,秦冰阳,司雯,等.混合粒子群优化小波自适应阈值估计算法及用于局部放电去噪[J].高电压技术,2017,43(5):1485-1492.
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[14] 赵雯雯,曾兴雯.一种新的EMD去噪方法[J].电子科技,2008,21(5):30-32,36.
[15] 赵志宏.基于振动信号的机械故障特征提取与诊断研究[D].北京:北京交通大学,2012.
[16] GAO H,LIANG L,CHEN X,et al.Feature extraction and recognition for rolling element bearing fault utilizing short-time fourier transform and non-negative matrix factorization[J].Chinese Journal of Mechanical Engineering,2015,28(1):96-105.
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[18] HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[C]//the Royal Society of Louleon A:Mathenatical,Physical and Engineering Sciences,1998,454:903-995.
[19] 黄建,胡晓光,巩玉楠.基于经验模态分解的高压断路器机械故障诊断方法[J].中国电机工程学报,2011,31(12):108-113.
[20] DU Q,YANG S.Application of the EMD method in the vibration analysis of ball bearings[J].Mechanical systems and Signal Processing,2007,21(6):2634-2644.
[21] 刘洋,曹云东,侯春光.基于经验模态分解及维格纳威尔分布的电缆双端故障定位算法[J].中国电机工程学报,2015,35(16):4086-4093.
[22] DONOHO D L,JOHNSTONE L.Adapting to unknown smoothness via wavelet shrinkage[J].Journal of American Statistical Association,1995,13(90):1201-1225.
[23] SAVIZKY A,GOLAY M J E.Smoothing and differentiation of databy simplified least squares procedures[J].Anal Chem,1964,36(8):1627-1639.
[2] 王珩,袁欢,何斌,等.交流接触器用触头材料研究综述[J].电器与能效管理技术,2018(3):1-4,29.
[3] 郑淑梅,李奎,刘政君,等.基于触头电弧侵蚀的交流接触器电寿命分布特征研究[J].中国电机工程学报,2017,37(22):6730-6739.
[4] 曹云东,高筱婷,刘树鑫,等.基于全寿命电器状态监测数据的特征信息提取[J].高电压技术,2016,42(9):2980-2987.
[5] 黄艳玲,司马文霞,杨庆,等.电力系统实测过电压信号的特征量提取与验证[J].高电压技术,2013,39(1):60-66.
[6] 李奎,李晓倍,郑淑梅,等.基于BP神经网络的交流接触器剩余电寿命预测[J].电工技术学报,2017,32(15):120-127.
[7] 朱顺华.基于多信息融合的交流接触器状态评估方法研究[D].沈阳:沈阳工业大学,2017.
[8] 李奎,段宇,黄少坡,等.基于Wiener过程的交流接触器剩余电寿命预测[J].中国电机工程学报,2018,38(13):3978-3986,4039.
[9] LI X,JIN J,SHEN Y,et al.Noise level estimation method with application to EMD-based signal denoising[J].Journal of Systems Engineering and Electronics,2016,27(4):763-771.
[10] 吕敬祥,刘国强.磁声电无损检测及改进的EMD消噪方法[J/OL].电工技术学报:1-9[2018-09-10].https://doi.org/10.19595/j.cnki.1000-6753.tces.171126.
[11] 李清泉,秦冰阳,司雯,等.混合粒子群优化小波自适应阈值估计算法及用于局部放电去噪[J].高电压技术,2017,43(5):1485-1492.
[12] 尹红艳,曹云东.改进的EMD消噪方法在交流接触器退化规律研究中的应用[J].电器与能效管理技术,2016(15):28-31.
[13] GONG W,LI J,MAO F,et al.Comparison of simultaneous signals obtained from a dual-field-of-view lidar and its application to noise reduction based on empirical mode decomposition[J].Chinese Optics Letters,2011,9(5):1-4.
[14] 赵雯雯,曾兴雯.一种新的EMD去噪方法[J].电子科技,2008,21(5):30-32,36.
[15] 赵志宏.基于振动信号的机械故障特征提取与诊断研究[D].北京:北京交通大学,2012.
[16] GAO H,LIANG L,CHEN X,et al.Feature extraction and recognition for rolling element bearing fault utilizing short-time fourier transform and non-negative matrix factorization[J].Chinese Journal of Mechanical Engineering,2015,28(1):96-105.
[17] 杜建卫.希尔伯特黄变换方法及其在特征提取中的应用研究[D].北京:北京科技大学,2017.
[18] HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[C]//the Royal Society of Louleon A:Mathenatical,Physical and Engineering Sciences,1998,454:903-995.
[19] 黄建,胡晓光,巩玉楠.基于经验模态分解的高压断路器机械故障诊断方法[J].中国电机工程学报,2011,31(12):108-113.
[20] DU Q,YANG S.Application of the EMD method in the vibration analysis of ball bearings[J].Mechanical systems and Signal Processing,2007,21(6):2634-2644.
[21] 刘洋,曹云东,侯春光.基于经验模态分解及维格纳威尔分布的电缆双端故障定位算法[J].中国电机工程学报,2015,35(16):4086-4093.
[22] DONOHO D L,JOHNSTONE L.Adapting to unknown smoothness via wavelet shrinkage[J].Journal of American Statistical Association,1995,13(90):1201-1225.
[23] SAVIZKY A,GOLAY M J E.Smoothing and differentiation of databy simplified least squares procedures[J].Anal Chem,1964,36(8):1627-1639.